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Shi Jie Tay

dblp:236/1363 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0003-0689-8408ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › structural bioinformatics › macromolecular structure analysis
glycan structure analysis
0.412019
GlycanAnalyzer: software for automated interpretation of N-glycan profiles after exoglycosidase digestions · Bioinform. 2019
Bioinformatics and computational biology
glycomics
0.412019
GlycanAnalyzer: software for automated interpretation of N-glycan profiles after exoglycosidase digestions · Bioinform. 2019

Methods — techniques the papers use, named apart from their topics

pattern matching · 0.4mass spectrometry · 0.4
YearPublicationVenuePosition
2019 GlycanAnalyzer: software for automated interpretation of N-glycan profiles after exoglycosidase digestions
abstract
SUMMARY: Many eukaryotic proteins are modified by N-glycans. Liquid chromatography (ultra-performance -UPLC and high-performance-HPLC) coupled with mass spectrometry (MS) is conventionally used to characterize N-glycan structures. Software can automatically assign glycan structures by matching their observed retention times and masses with standardized values in reference databases. However, more precise confirmation of N-glycan structures can be derived using exoglycosidases, enzymes that remove specific monosaccharides from glycans. Exoglycosidase removal of monosaccharides results in signature peak shifts, in both UPLC and MS1, yielding an effective way to verify N-glycan structure with high detail (down to the position and isomeric linkage of each monosaccharide). Because manual interpretation of exoglycosidase data is complex and time consuming, we developed GlycanAnalyzer, a web application that pattern matches N-glycan peak shifts following exoglycosidase digestion and automates structure assignments. GlycanAnalyzer significantly improves assignment accuracy over other auto-assignment methods on tests with a monoclonal antibody and four glycan standards (100% versus 82% for the next best software). By automating data interpretation, GlycanAnalyzer enables the easier use of exoglycosidases to precisely define N-glycan structure. AVAILABILITY AND IMPLEMENTATION: http://glycananalyzer.neb.com. Datasets available online. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Ian Walsh, Terry Nguyen-Khuong, Katherine Wongtrakul-Kish, Shi Jie Tay, Daniel Chew, Tasha José, Christopher H. Taron, Pauline M. Rudd
Bioinform.4
2019 GlycanAnalyzer: software for automated interpretation of N-glycan profiles after exoglycosidase digestions
abstract
Bioinformatics (2019) doi: 10.1093/bioinformatics/bty681, 35, 688–690. In the original article, author Tasha José’s first and surname were originally transposed. This has now been corrected.
Ian Walsh, Terry Nguyen-Khuong, Katherine Wongtrakul-Kish, Shi Jie Tay, Daniel Chew, Tasha José, Christopher H. Taron, Pauline M. Rudd
Bioinform.4